An updated meta-analysis showed smoking modify the association of GSTM1 null genotype on the risk of coronary heart disease

Genetic Polymorphisms and Genetic Risk Scores Contribute to the Risk of Coronary Artery Disease (CAD) in a North Indian Population

Coronary artery disease (CAD) is the leading cause of death in India. Many genetic polymorphisms play a role in regulating oxidative stress, blood pressure and lipid metabolism, contributing to the pathophysiology of CAD. This study examined the association between ten polymorphisms and CAD in the Jat Sikh population from Northern India, also considering polygenic risk scores. This study included 177 CAD cases and 175 healthy controls. The genetic information of GSTM1 (rs366631), GSTT1 (rs17856199), ACE (rs4646994), AGT M235T (rs699), AGT T174M (rs4762), AGTR1 A1166C (rs5186), APOA5 (rs3135506), APOC3 (rs5128), APOE (rs7412) and APOE (rs429358) and clinical information was collated. Statistical analyses were performed using SPSS version 27.0 and SNPstats. Significant independent associations were found for GST*M1, GST*T1, ACE, AGT M235T, AGT T174M, AGTR1 A1166C and APOA5 polymorphisms and CAD risk (all p < 0.05). The AGT CT haplotype was significantly associated with a higher CAD risk, even after controlling for covariates (adjusted OR = 3.93, 95% CI [2.39-6.48], p < 0.0001). The APOA5/C3 CC haplotype was also significantly associated with CAD (adjusted OR = 1.86, 95% CI [1.14-3.03], p < 0.05). A higher polygenic risk score was associated with increased CAD risk (adjusted OR = 1.98, 95% CI [1.68-2.34], p < 0.001). Seven polymorphisms were independently associated with an increase in the risk of CAD in this North Indian population. A considerable risk association of AGT, APOA5/C3 haplotypes and higher genetic risk scores is documented, which may have implications for clinical and public health applications.

Genetic Polymorphisms of GSTM1 and GPX1 Genes and Smoking Susceptibility in the Saudi Population

Background/Objective/Methods

Glutathione-S-transferase Mu1 (GSTM1) and glutathione peroxidase 1 (GPX1) are known antioxidant enzymes that help protect cells from the oxidative damage that occurs from smoking. This study explored the correlation between GSTM1 and GPX1 levels between a group of smokers with the GSTM1 and GPX1 genes in the Saudi population and a control group and investigated the genetic risk factors in the group of smokers.

Results

The control and smokers' group (n = 50; aged 22.3 ± 3.1 years; BMI 24.6 ± 5.9 kg/m2) were genotyped using quantitative polymerase chain reaction (qPCR). In comparison with the control group, the smokers' group displayed a different genotype disruption of GSTM1 and GPX1. Carriers of the homozygous (TT) genotype of GSTM1 had more than a twofold (OR = 2.71, 95% CI = 0.10-70.79, P = 1.000) smoking risk than the carriers of the heterozygous (CT) genotype. Those with the GPX1 gene showed no risk in the control and smokers' groups. Smokers with the TT/GG combination (homozygous for GPX1 and normal for GPX1) were identified as high risk (OR = 2.58, 95% CI = 0.096-69.341).

Conclusion

The main outcomes showed no significant association between genetic polymorphism of the GSTM1 and GPX1 genes and cigarette smoking in the Saudi Arabian population. However, the results showed a slight decrease in the number of GSTM1 and GPX1 gene modifications among smokers.

Gpx3 and Egr1 Are Involved in Regulating the Differentiation Fate of Cardiac Fibroblasts under Pressure Overload

Objectives

Although myocardial fibrosis is a common pathophysiological process associated with many heart diseases, the molecular mechanisms regulating the development of fibrosis have not been fully determined. Recently, single cell RNA sequencing (scRNA-seq) analysis has been used to examine cellular fate and function during cellular differentiation and has contributed to elucidating the mechanisms of various diseases. The main purpose of this study was to characterize the fate of cardiac fibroblasts (CFs) and the dynamic gene expression patterns in a model of cardiac pressure overload using scRNA-seq analysis.

Methods

The public scRNA-seq dataset of the transverse aortic coarctation (TAC) model in mice was downloaded from the GEO database, GSE155882. First, we performed quality control, dimensionality reduction, clustering, and annotation of the data through the Seurat R package (v4.0.5). Then, we constructed the pseudotime trajectory of cell development and identified key regulatory genes using the Monocle R package (v2.22.0). Different cell fates and groups were fully characterized by Gene Set Enrichment Analysis (GSEA) analysis and Transcription factor (TF) activity analysis. Finally, we used Cytoscape (3.9.1) to extensively examine the gene regulatory network related to cell fate.

Results

Pseudotime analysis showed that CFs differentiated into two distinct cell fates, one of which produced activated myofibroblasts, and the other which produced protective cells that were associated with reduced fibrosis levels, increased antioxidative stress responses, and the ability to promote angiogenesis. In the TAC model, activated CFs were significantly upregulated, while protective cells were downregulated. Treatment with the bromodomain inhibitor JQ1 reversed this change and improved fibrosis. Analysis of dynamic gene expression revealed that Gpx3 was significantly upregulated during cell differentiation into protective cells. Gpx3 expression was affected by JQ1 treatment. Furthermore, Gpx3 expression levels were negatively correlated with the different levels of fibrosis observed in the various treatment groups. Finally, we found that transcription factors Jun, Fos, Atf3, and Egr1 were upregulated in protective cells, especially Egr1 was predicted to be involved in the regulation of genes related to antioxidant stress and angiogenesis, suggesting a role in promoting differentiation into this cell phenotype.

Conclusions

The scRNA-seq analysis was used to characterize the dynamic changes associated with fibroblast differentiation and identified Gpx3 as a factor that might be involved in the regulation of myocardial fibrosis under cardiac pressure overload. These findings will help to further understanding of the mechanism of fibrosis and provide potential intervention targets.

Contribution of Glutathione-S-Transferases Polymorphism and Risk of Coronary Artery Diseases: A Meta-Analysis

BACKGROUND

Oxidative stress is one of the risk components in the development of coronary artery diseases (CAD) and polymorphism in major antioxidant genes like Glutathione-S-Transferases (GST) has been associated with the increased CAD susceptibility and severity.

OBJECTIVE

To get a precise evaluation and to update the association, a meta-analysis on GST (GSTM1, GSTT1 and GSTP1) polymorphism with CAD was performed. Moreover, the combined effect of GSTM1/GSTT1 null genotypes on CAD risk which is not yet studied so far but it has the highest risk of developing diseases.

MATERIALS AND METHOD

PubMed, Embase and Web of Science were systematically searched for eligible studies. Case-control studies with genotypic frequency, provide data to calculate odds ratio (OR) and in English language were selected. OR with 95% C.I was calculated and random effect model was used. NOS scale was used to asses the qulity of the included studies.

RESULTS

Meta-analysis indicated that the GSTM1 null genotype and GSTP1 (Ile105Val) polymorphism is significantly associated with CAD risk with a pooled OR-1.38, p=0.01 for GSTM1 and OR-1.19, p=0.04 for GSTP1. Dual null genotype of GSTM1-GSTT1 has highest risk for CAD development (OR-1.59, p=0.003) and there is no significant association for GSTT1 null genotype with CAD. In the subgroup analysis, GSTM1 showed the increased risk for Asians (OR-1.68, p=<0.01) and smokers (OR-1.98, p=<0.01). Publication bias was not observed.

CONCLUSION

The findings suggests that the GSTM1/GSTP1 polymorphism can be a predictive factor for CAD risk and a larger sample size is required further to confirm the association.

Association of GSTP1 Ile105Val polymorphism with the risk of coronary heart disease: An updated meta-analysis

Background

Numerous case-control studies have investigated the association between GSTP1 Ile105Val polymorphism and CHD risk, but the results from published studies were inconclusive. The present meta-analysis was performed to derive a more precise estimation.

Methods

PubMed, EMBASE, and Web of Science database searches were conducted to retrieve relevant articles.

Results

Ultimately, 5,451 CHD cases and 5,561 controls from 15 studies were included. Pooled analysis did not yield any statistically significant association between GSTP1 Ile105Val polymorphism and CHD risk for the overall population (Val vs. Ile: OR, 1.05; 95% CI, 0.93 to 1.18; Val/Val vs. Ile/Ile: OR, 1.09; 95% CI, 0.83 to 1.42; Val/Ile vs. Ile/Ile: OR, 1.09; 95% CI, 0.93 to 1.28; Val/Val vs. Val/Ile+Ile/Ile: OR, 1.04; 95% CI, 0.83 to 1.30; Val/Val+Val/Ile vs. Ile/Ile: OR, 1.14; 95% CI, 0.97 to 1.33). Subgroup analyses and sensitivity analyses indicated that GSTP1 Ile105Val polymorphism was still not associated with an increased risk of CHD. After excluding studies detected by Galbraith plots as major sources of heterogeneity, these relationships were still not significant.

Conclusions

The overall results did not reveal a major role of the GSTP1 Ile105Val polymorphism in modulating CHD risk. Well-designed studies with large sample sizes are needed to validate our findings and explore the possible gene-gene or gene-environment interactions.

Assessment of Cardiovascular Risk Factors and Their Interactions in the Risk of Coronary Heart Disease in Patients with Type 2 Diabetes with Different Weight Levels, 2013-2018

PURPOSE

In addition to hyperglycemia and hyperlipidemia, obesity and hypertension are important cardiovascular risk factors for coronary heart disease (CHD) in patients with type 2 diabetes mellitus (T2DM). This study aims to explore the interaction of these risk factors.

PATIENTS AND METHODS

Data of hospitalized patients with T2DM from 2013 to 2018 were collected. A multivariate logistic regression model was established. Patients with normal weight and blood pressure were recruited as controls. The interaction on the risk of CHD was evaluated by relative excess risk due to interaction (RERI).

RESULTS

Among the 30,693 patients with T2DM, 7202 (23.5%) had CHD. In the low weight group, the prevalence of CHD in patients with hypertension was nearly four times higher than that in patients without hypertension (42.7% vs 11.3%, P < 0.01). The OR value of hypertension alone on CHD increased from 1.29 (95% CI 1.06-1.56) in the body mass index (BMI) 30.0-34.9 kg/m² group to 1.35 (95% CI 1.11-1.62) in the BMI ≤ 18.5 kg/m² group. Additive interaction was observed between hypertension and BMI in CHD risk, especially in the low weight group (RERI:2.2, 95% CI 0.9-3.5). BMI and CHD risk showed a smile curve relationship. The attributive proportion in the low weight group was higher than that in the severe obesity group, that is, 0.52 (95% CI 0.35-0.69) vs 0.18 (95% CI -0.59 to 0.95).

CONCLUSION

Maintaining normal weight and avoiding low weight are particularly important for patients with co-occurring diabetes and hypertension to prevent the risk of CHD.